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      ADAM12 is a costimulatory molecule that determines Th1 cell fate and mediates tissue inflammation

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          Abstract

          A disintegrin and metalloproteinase (ADAM)12 was previously found to be expressed in T cells in the inflamed brain. However, the function of ADAM12 in T-cell responses in general and in tissue inflammation has not been examined. Here, we studied the role of ADAM12 in T-cell responses, fate determination on activation, and its functions in T cells to mediate tissue inflammation. We identified ADAM12 as a costimulatory molecule that is expressed on naive T cells and downregulated on stimulation. ADAM12 mimics CD28 costimulatory signaling to activate and induce the proliferation of T-helper 1 (Th1) cells. Monoclonal ADAM12 Fab antibodies trigger T-cell activation by amplifying TCR signaling to stimulate T-bet-mediated IFNγ production. Lack of genomic ADAM12 and its knockdown in T cells diminished T-bet and IFNγ production in Th1 cells, whereas other T cells, including Th17 cells, were unaffected. ADAM12 had similar functions in vivo on myelin antigen (MOG 35–55)-induced T-cell activation. We found that genetic loss of ADAM12 profoundly alleviated Th1-mediated neuroinflammation and thus disease severity in experimental autoimmune encephalomyelitis, a model of multiple sclerosis. Transcriptomic profiling of MOG 35–55-specific ADAM12 −/− T cells revealed differentially expressed genes that are important for T-cell activation, proliferation, and costimulatory signaling and Th1 pathogenicity, consistent with their inability to cause T-cell-mediated skin inflammation in a model of adoptive delayed-type hypersensitivity. We conclude that ADAM12 is a T-cell costimulatory molecule that contributes to the pathogenesis of tissue inflammation and a potential target for the treatment of Th1-mediated diseases.

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Full-length RNA-seq from single cells using Smart-seq2.

            Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ∼2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1-3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA(-)) RNA.
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              Conversion of Peripheral CD4+CD25− Naive T Cells to CD4+CD25+ Regulatory T Cells by TGF-β Induction of Transcription Factor Foxp3

              CD4+CD25+ regulatory T cells (Treg) are instrumental in the maintenance of immunological tolerance. One critical question is whether Treg can only be generated in the thymus or can differentiate from peripheral CD4+CD25− naive T cells. In this paper, we present novel evidence that conversion of naive peripheral CD4+CD25− T cells into anergic/suppressor cells that are CD25+, CD45RB−/low and intracellular CTLA-4+ can be achieved through costimulation with T cell receptors (TCRs) and transforming growth factor β (TGF-β). Although transcription factor Foxp3 has been shown recently to be associated with the development of Treg, the physiological inducers for Foxp3 gene expression remain a mystery. TGF-β induced Foxp3 gene expression in TCR-challenged CD4+CD25− naive T cells, which mediated their transition toward a regulatory T cell phenotype with potent immunosuppressive potential. These converted anergic/suppressor cells are not only unresponsive to TCR stimulation and produce neither T helper cell 1 nor T helper cell 2 cytokines but they also express TGF-β and inhibit normal T cell proliferation in vitro. More importantly, in an ovalbumin peptide TCR transgenic adoptive transfer model, TGF-β–converted transgenic CD4+CD25+ suppressor cells proliferated in response to immunization and inhibited antigen-specific naive CD4+ T cell expansion in vivo. Finally, in a murine asthma model, coadministration of these TGF-β–induced suppressor T cells prevented house dust mite–induced allergic pathogenesis in lungs.
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                Author and article information

                Contributors
                shohreh.issazadeh@bric.ku.dk
                Journal
                Cell Mol Immunol
                Cell Mol Immunol
                Cellular and Molecular Immunology
                Nature Publishing Group UK (London )
                1672-7681
                2042-0226
                22 June 2020
                22 June 2020
                August 2021
                : 18
                : 8
                : 1904-1919
                Affiliations
                [1 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Neuroinflammation Unit, Biotech Research & Innovation Centre (BRIC), Faculty of Health and Medical Sciences, , University of Copenhagen, ; Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
                [2 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, BRIC, Faculty of Health and Medical Sciences, , University of Copenhagen, ; Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
                Author information
                http://orcid.org/0000-0002-1293-1019
                Article
                486
                10.1038/s41423-020-0486-8
                8322154
                32572163
                cbfae1d1-c280-45e8-9527-4579a55f0dd3
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 January 2020
                : 31 May 2020
                Funding
                Funded by: This study was supported from The Danish Council For Independent Research (DFF)-Medical Science (DFF-4183-00427B), The Danish Multiple Sclerosis Society, and The Lundbeck Foundation to S. Issazadeh-Navikas.
                Funded by: MS Internation Federation-McDonald Fellowship
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to CSI and USTC 2021

                Immunology
                t cells,t-bet,th17,eae,dth,gm-csf,inflammation,immunology
                Immunology
                t cells, t-bet, th17, eae, dth, gm-csf, inflammation, immunology

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